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Exploring Impacts to COVID-19 Herd Immunity Thresholds Under Demographic Heterogeneity that Lowers Vaccine Effectiveness
Chloé Flore Paris; Julie Allison Spencer; Lauren A Castro; Sara Y Del Valle.
Afiliação
  • Chloé Flore Paris; Los Alamos National Laboratory, Information Systems and Modeling
  • Julie Allison Spencer; Los Alamos National Laboratory, Information Systems and Modeling
  • Lauren A Castro; Los Alamos National Laboratory, Information Systems and Modeling
  • Sara Y Del Valle; Los Alamos National Laboratory, Information Systems and Modeling
Preprint em Inglês | medRxiv | ID: ppmedrxiv-22277763
ABSTRACT
The COVID-19 pandemic has caused severe health, economic, and societal impacts across the globe. Although highly efficacious vaccines were developed at an unprecedented rate, the heterogeneity in vaccinated populations has reduced the ability to achieve herd immunity. Specifically, as of Spring 2022, the 0-4 year-old population is still unable to be vaccinated and vaccination rates across 5-11 year olds are low. Additionally, vaccine hesitancy for older populations has further stalled efforts to reach herd immunity thresholds. This heterogeneous vaccine landscape increases the challenge of anticipating disease spread in a population. We developed an age-structured Susceptible-Infectious-Recovered-type mathematical model to investigate the impacts of unvaccinated subpopulations on herd immunity. The model considers two types of undervaccination - age-related and behavior-related - by incorporating four age groups based on available FDA-approved vaccines. The model accounts for two different types of vaccines, mRNA (e.g., Pfizer, Moderna) and vector (e.g., Johnson and Johnson), as well as their effectiveness. Our goal is to analyze different scenarios to quantify which subpopulations and vaccine characteristics (e.g., rate or efficacy) most impact infection levels in the United States, using the state of New Mexico as an example.
Licença
cc_by_nc
Texto completo: Disponível Coleções: Preprints Base de dados: medRxiv Tipo de estudo: Experimental_studies / Rct Idioma: Inglês Ano de publicação: 2022 Tipo de documento: Preprint
Texto completo: Disponível Coleções: Preprints Base de dados: medRxiv Tipo de estudo: Experimental_studies / Rct Idioma: Inglês Ano de publicação: 2022 Tipo de documento: Preprint
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